Prerequisites
Before
attending this course, students must have:
-
Conceptual
understanding of OLAP solutions.
-
Experience
navigating the Microsoft Windows Server environment.
-
Experience
with Windows services (starting and stopping).
-
Experience
creating service accounts and permissions.
-
Experience
with Microsoft SQL Server, including:
-
SQL
Server Agent.
-
SQL
Server query language (SELECT, UPDATE, INSERT, and DELETE).
-
SQL
Server System tables.
-
SQL
Server accounts (users and permissions).
Audience
Profile
The primary
audience for this course is individuals who design and maintain business
intelligence solutions for their organization. These individuals work in
environments where databases play a key role in their primary job and may
perform database administration and maintenance as part of their primary job
responsibilities.
The secondary
audience for this course is individuals who develop applications that deliver
content from SQL Server Analysis Services to the organization.
At Course
Completion
After
completing this course, students will be able to:
-
Describe
how SQL Server Analysis Services can be used to implement analytical
solutions.
-
Create
multidimensional analysis solutions with SQL Server Analysis
Services.
-
Implement
dimensions and cubes in an Analysis Services solution.
-
Implement
measures and measure groups in an Analysis Services solution.
-
Query
a multidimensional Analysis Services solution.
-
Customize
an Analysis Services cube.
-
Deploy
and secure an Analysis Services database.
-
Maintain
a multidimensional Analysis Services solution.
-
Implement
a Data Mining solution
Course
Outline
Module 1: Introduction to Microsoft SQL Server Analysis
Services
Module 2: Creating Multidimensional Analysis Solutions
Module 3: Working with Cubes and Dimensions
Module 4: Working with Measures and Measure Groups
Module 5: Querying Multidimensional Analysis Solutions
Module 6: Customizing Cube Functionality
Module 7: Deploying and Securing an Analysis Services
Database
Module 8: Maintaining a Multidimensional
Solution
Module 9: Introduction
to Data Mining